Cox Proportional Hazards Model

Halley Deleeuw and Jasmine Sawh

2023-11-30

Introduction to Cox Proportional Hazards Model

  • Developed by Sir David R. Cox in 1972
  • Statistical method for survival analysis and epidemiological research
  • Analyzes time-to-event data
  • Estimates hazard function
  • Explores relationships with independent variables
  • Applications include healthcare, engineering, social sciences

Methods

  • Semiparametric survival analysis method
  • Right-censored data \[ λ(t) = λ0(t) * exp(β₁X₁ + β₂X₂ + ... + βₖ) \]

Assumptions/Limitations

  • Proportional Hazard Assumption
  • Linearity of Continuous Variables
  • Independence of Censoring
  • Sensitivity to Outliers

Data Description

  • National Cancer Institute Surveillance, Epidemiology, and End Results Program (SEER)
  • Comprehensive cancer surveillance system in the US
  • Covers a wide range of demographic information
  • Provides insights into cancer trends, outcomes, and risk factors at a national level

Data Table

#Data Visualizations

Objective and Purpose

  • Explore factors impacting patient survival
  • Analyze key variables such as cancer type, race, gender, age
  • Understanding their significance in predicting survival
  • Assess hazard ratios for each variable
  • Center analysis on relationships and impact on survival outcomes

Statistical Modeling for Data

Stratified Analysis